In a responsive load service power consumption of devices connected to an electrical power grid is managed to respond to imbalance between power generated and power consumed across the power grid. A power grid which implements a responsive load service is sometimes referred as a ‘smart’ electrical grid. The responsive load service may be delivered by means of a centralised controller that monitors the power grid and responds to detected grid imbalances by communicating with groups of loads and/or individual loads to adjust their power consumption. Autonomous responsive loads may additionally or alternatively be used to deliver a responsive load service. Autonomous responsive loads independently monitor a measurable parameter of the power grid, such as frequency, fluctuations of which are indicative of a grid imbalance. The autonomous responsive loads automatically respond to detected fluctuations by adjusting their power consumption.
To smooth the power consumption adjustment response of a responsive load service and to avoid load synchronisation, a series or range of measurable grid imbalances (e.g. grid frequencies) can be used as triggers for an individual load and/or a group of loads to adjust their power consumption. In the case of autonomous responsive loads the degree of grid imbalance at which an individual load and/or group of loads is to be triggered is referred to herein as the load or loads “willingness to switch”. The degree of grid imbalance at which a load or a group of loads are triggered to adjust their power consumption may be allocated randomly. However, a random allocation can result in some responsive loads tending to adjust their power consumption more often than other responsive loads within the responsive load population, which can be undesirable.
Certain types of power consuming devices such as, but not limited to, refrigerators, can be limited in their ability to deliver on demand power consumption changes as a result of their duty cycle. For such power consuming devices a measured variable (such as refrigerator internal temperature) can be used as a marker for the state of the device within its duty cycle. This measured variable is representative of the device's availability for delivering a responsive load service and in GB 2426878 is used in determining trigger grid frequencies across a population of power consuming devices, i.e. their ‘willingness to switch’. Thus, a range of trigger frequencies can be allocated to ‘less available’ devices to ensure that these devices only adjust their power consumption during extreme grid frequency excursions. The resulting response of the total population of responsive loads is roughly linear with respect to frequency because for each device in the population of devices its duty cycle position should be random (if the duty cycles of power consuming devices within a population of devices become synchronised, the response becomes significantly non-linear).
Some power consuming devices operate in a very slow (timescale of a day) duty cycle or have no clearly defined duty cycle. Examples of such devices include heaters and ventilators. Such devices may be operated continuously in order to maintain air freshness but as part of a responsive load service can be turned off or turned up to a higher setting for a short period of time without adverse consequences. For these devices there is no obvious measured variable of the power grid that can be used to derive a “willingness to switch” trigger or a measured variable that would be randomly distributed across a population of such devices. It has been presumed that alterations to the normal power consumption behaviour of the devices should occur as rarely as possible and for as little time as possible, while meeting responsive load service requirements.
For a responsive load service utilising devices with no clearly defined duty cycle or long duration duty cycles, to date the approach has essentially involved randomly assigning to devices triggering frequencies in the applicable frequency range. This random assignment has been used in association with a plurality of behaviour rules, such as one or more of the following: minimum times for action; maximum times for action; etc.
A problem with the above approach, as revealed by modelling, is that the “load change” (be it increase or decrease) is not “fairly” shared across all devices. Devices with triggering frequencies far from the nominal frequency of the power grid are unlikely ever to be triggered. Whereas devices with trigger frequencies near to the nominal frequency of the power grid are likely to be triggered very frequently (perhaps every few minutes at times). Frequent triggering of a device can be prevented through the use of behaviour rules (e.g. no retriggering within 30 minutes) but the resultant performance of the responsive load service is generally unsatisfactory with poor tracking of frequency excursions.
Moreover, it has been found that resetting randomly assigned frequencies cannot fully solve this problem unless trigger resetting happens on a timescale of under an hour. However frequent (i.e. <60 mins) trigger resetting has other attendant problems and does not guarantee that the new trigger frequency assigned to a device is significantly different from the previous one, unless systematic rules to ensure this are used.
A centrally controlled responsive load service is described in U.S. Pat. No. 4,064,485 in which a plurality of different groups of responsive load are used to deliver a responsive load service. In U.S. Pat. No. 4,064,485 a first group of responsive loads are used in the delivery of a responsive load service in a predetermined order. In a second group of responsive loads, the loads are used to deliver the responsive load service in rotation. With the first group of loads, the same responsive load is always used first and inevitably will be used much more often than other responsive loads later in the group.